• John Griffiths

( With essential contributions from: Julie Courtiol, Amanda Easson, Kelly Shen, Jerry Jeyachandra )

1. Log into on the scinet jupyterhub website

2. First time only: add the course's conda env to your conda envs list:

Open up a terminal from the jupyterhub landing page

module load intelpython3
conda config --append envs_dirs /scinet/course/ss2020/8_brainnetwork/env

Return the the landing page and refresh the browser. You should see the ss2020_tvb option now when clicking the new menu on the top right

3. Also first time only: clone the github repo for the course in a terminal

git clone https://github.com/JohnGriffiths/ScinetSS2020_BrainNetworkModelling

4. Navigate to the notebooks folder in the downloaded github repo folder, and open up the course notebooks

Click on the Open In Binder badge above, and wait patiently for the image and environment to be built and initiated.

Click on the Open In Colab badge above, and wait patiently for the environment to be initiated.

Note - in google colab you need to pip install non-standard libraries. Each of the notebooks has a commented out section that needs to be un-commented and run in order to make the libraries available on Colab.

See here for the scinet course webpage

To access the jupyterhub:

• Click 'log in' in the top right. Enter your login details
• From the course website, click 'login information for cluster'
• Follow the instructions: go to the scinet jupyterhub site, and enter the uname/pwd displayed on the previous page
• Follow the jupyterhub instructions above

The homework assignment for the course can be found in notebooks/homework_assignment.ipynb

This follows on from the intro_to_whole_brain_modelling.ipynb notebook, which is the basis of the practical session.

Completed assignments should be uploaded to the designated folder on the course website.

These should take the form of jupyter notebooks that are extended from homework_assignment.ipynb.